Research On Scrap Steelmaking And Continuous Casting Production Scheduling Problem For Energy Saving And Carbon Reduction

The steel industry strives to resolve overcapacity,improve green development,and upgrade industrial transformation.Concerning the bottleneck of iron and steel scrap remanufacturing,the iron and steel scrap steelmaking and continuous casting process needs to consider the interdependency of the cost of electricity and the price ladder,the relevance of carbon emissions for the production process,and the harmony between the rhythm of production and flexibility during the process.Scheduling the iron and steel scrap steelmaking and continuous casting process to aim at power savings and carbon emissions reduction,not only could improve the production efficiency of steelmaking equipment and regulating the production rhythm,but also reduce environmental emissions and electricity costs,thus improve the competitiveness of steel products.Considering the scheduling optimization of iron and steel scrap steelmaking and continuous casting process aiming at power saving and carbon emissions reducing,not only the multiple performance indexes of the production process need to be satisfied,but also the impact of time-of-use electricity price and carbon emissions of different equipment on energy consumption in production scheduling process should be taken into account.However,due to the multi-conflict uncertainties of production equipment and the multi-coupling characteristics of multi-performance indexes,it is difficult to describe the scheduling process through accurate mathematical models;meanwhile,providing that the existing methods are directly applied to the large-scale,multi-objective,multi-constraints and multi-variables iron and steel scrap steelmaking-continuous casting production scheduling problem,it is difficult to guarantee the efficiency requirement of the scheduling optimization process because of the large storage space and slow calculation time.How to scientifically build scheduling mathematical models in accord with practical production,and propose a more practical scheduling optimization strategy in order to reduce the computational scale and the computational difficulty as the core research content of algorithms,become the key problems to the scheduling optimization problem.In order to solve the difficulties of the problem mentioned above,based on the support from the National Natural Science Foundation of China-General Program(Grant No.61873174)"Research on Integrated Optimization Method of Order Planning and Production Scheduling for the Steelmaking-Continuous Casting Process under Uncertainties" and National Natural Science Foundation of China-Young Program(Grant No.61503259)"Research on Main and Accessorial Equipment Scheduling Method for the Steelmaking-Continuous Casting Process Based on Effective Lagrange Relaxation Iterative Algorithm",this paper proposed the research on scheduling of iron and steel scrap steelmaking and continuous casting process aiming at power saving and carbon emissions reducing under the improved Augmented Lagrangian relaxation framework.The major contributions are listed as follows:1.Based on the scheduling of iron and steel scrap steelmaking and continuous casting process in a large domestic iron and steel enterprise,this paper establishes the power cost measurement model and the carbon emission measurement model for this production process.Combined with multiple performance indexes for the scheduling optimization of steelmaking and continuous casting process,this paper constructs the mixed-integer programming mathematical model with separable structure characteristics for the scheduling of the iron and steel scrap steelmaking and continuous casting process aiming at power savings and carbon emissions reduction.2.This paper proposes the synergistic integration strategy of surrogate subgradient Lagrangian algorithm with controllable gradient direction and steps and backward dynamic programming with controllable processing time under the linearization Augmented Lagrangian relaxation framework.This strategy effectively overcomes the difficult problem that the traditional Augmented Lagrangian relaxation algorithm cannot be divided into sub-problems due to the introduction of the second penalty term;solves the flexible problem with uncertain processing time in the scheduling optimization process;ensures a smaller intersection angle between the gradient and the optimal direction,reduces the number of iterations in the iteration process,and improves the optimization efficiency for the scheduling of iron and steel scrap steelmaking and continuous casting.3.The industrial experiments for the proposed approach are tested based on the data from the real steelmaking plant.The validity of the mathematic model and the solution method are verified by the comparative experiments.The research improves the scheduling methods of actual iron and steel scrap re-melting production,promotes the model decomposition,analysis,and optimization techniques with the separable structure characteristics,and lays a foundation in the industry application for the scheduling theory.